JMIR Publications

ABSTRACT

Background:

Human voice has increasingly been recognized as an effective indicator for the detection of cognitive disorders. However, the association of acoustic features with specific cognitive function and mild cognitive impairment (MCI) have yet to be evaluated in a large community-based population.

Objective:

Our aim is to investigate the association between acoustic features and neuropsychological (NP) tests across multiple cognitive domains, and evaluate the added predictive power of acoustic composite scores for the classification of MCI.

Methods:

This study included dementia-free participants from the Framingham Heart Study, a large community-based cohort with longitudinal cognitive surveillance. For each participant, 65 low-level acoustic descriptors were derived from voice recordings of NP test administration. The associations between individual acoustic descriptors and 18 NP tests were assessed with linear mixed-effect models adjusted for age, sex, and education. Acoustic composite scores were then built by combining acoustic features significantly associated with NP tests. The added prediction power of acoustic composite scores for prevalent and incident MCI was also evaluated.

Results:

The study included 7,874 voice recordings from 4,950 participants (age 62 ± 14 years, 55.1% women), of whom 453 were diagnosed with MCI. Eight NP tests were associated with more than 15 acoustic features after adjusting for multiple testing. Four of the acoustic composite scores were significantly associated with prevalent MCI and seven were associated with incident MCI. The acoustic composite scores can increase the AUC of the baseline model for MCI prediction from 0.706 to 0.752.

Conclusions:

Multiple acoustic features are significantly associated with NP test performance and MCI, which can potentially be used as biomarkers for early cognitive impairment monitoring.